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International Journal of Economics, Commerce and Management United Kingdom Vol. II, Issue 12, Dec 2014

Licensed under Creative Common

http://ijecm.co.uk/ ISSN 2348 0386

INFLATION DYNAMICS AND GOVERNMENT SIZE IN NIGERIA

BigBen Chukwuma Ogbonna

Department of Economics, Ebonyi State University, Abakaliki, Nigeria

[email protected]

Abstract

The objective of this paper is to gauge the correlation between government size and

developments in consumer price index with recourse to Nigeria for the period of 1981-2013. The

study was implemented within the frame-work of the so called systems equations, founded on

co-integration and vector error correction model (VECM) methods. The results indicate that: (i)

Long run equilibrium relationship exist between consumer price index and government size in

Nigeria. (ii) No long run causal relationship was identified between consumer price index and

government expenditure in Nigeria. (iii) There is no short run causality running from government

expenditures to consumer price index in Nigeria. The results further suggest that a development

in consumer price index in Nigeria is a function of its previous period values (inflationary

expectations) and exchange rate of the domestic currency, meaning that the much touted

assumption by policy makers in Nigeria, that government size causes inflation, is not supported

by this enquiry. The above results present some policy implications that government of Nigeria

cannot comfortably regulate the levels of inflation in the economy by moderating the level of its

expenditures. This suggests that government expenditure should not be intended for the

moderation of developments in consumer price index, rather, Policy measures designed to

ensure effective and appropriate pricing of the domestic currency should be put in place for

effective control of inflation in Nigeria.

Keywords: Government size, Inflation, Co-integration, VECM, Causality Test, Nigeria

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© BigBen


INTRODUCTION

The use of fiscal policy as a measure for the control of inflation rates has received close

consideration in the debates among economists; (see: Ruge-Murcia, 1999, Yunus and

Giovanni, 2011, & Dimitrios, 2010) amongst others. They are of the view that certain fiscal

indicators contain additional statistically significant information to explain the variation on

inflation rates and to this extent demonstrate that the level of inflation is strongly correlated with

the level of public expenditure and vice versa. Further analysis of this correlation can also be

seen, instead, from the perspective of what is designated as “Patinkin effect”. For Don Patinkin,

inflation also has a negative impact on the fiscal deficit, through the negative effect it produces

in public spending (Patinkin, 1993). For some other authors, the correlation between inflation

and government size are more often in the hyperinflation economies, and even for these

economies, this association is apparent only during periods of high inflation, else this

relationship become inconsequential in the economies of low inflation; (See: Luis & Marco,

2005, 2001, Carlos al., 2002). The emerging economies have had their own share of empirical

studies addressing the issue of the effects of fiscal policy on growth and inflation. While some

of studies identified a close relationship between these variables either way, i.e positively or

negative (see, Sanjeev et al., 2005, Dhaneshwar, 1995, Shantayyanan et al., 1996, Abu-Qarn,

2003,), some other studies failed to identify any significant association between the duos (see:

Dakurah et al., 2001, Abizadeh & Yousefi, 1998) amongst others.

Generally, the inflation rate may at any point in time be used as a measure of the price

stability in an economy and theoretically, reflects the general rise in prices of goods and

services which can be decomposed into demand pull and cost push inflation. The objective of

exchange rate policy was derived from the overall objective of macroeconomic management, to

achieve internal and external balance in the medium term. Internal balance means the level of

economic activity consistent with the satisfactory level of inflation (Williamson, 1982),

In the system of floating exchange rates, exchange rate fluctuations can have a strong

impact on the level of prices through the aggregate demand (AD) and aggregate supply (AS).

On the aggregate supply, depreciation (devaluation) of domestic currency can affect the price

level directly through imported goods that domestic consumers pay. However, this condition

occurs if the country is an international price taker. Non direct influence from the depreciation

(devaluation) of currency against the price level of a country can be seen from the price of

capital goods (intermediate goods) imported by the manufacturer as an input. The weakening of

exchange rate will cause the price of inputs to be more expensive, thus contributing to a higher

cost of production. Manufacturers will certainly reflect the increase in cost in the prices of goods

International Journal of Economics, Commerce and Management, United Kingdom


that will be paid by consumers. As a result, the aggregate price level in the country increases or

if it continues it will cause inflation (Achsani, et. al, 2010).

For the few years past in the economic history of Nigeria, the pace of economic growth

appear to be epileptic but government expenditure as a proportion of gross domestic product

has kept a rising profile and the trend of inflation rate appears to be on the path of increase.

Central Bank of Nigeria’s Statistical Bulletin 2012 as published in 2013, shows percentage

innovations in aggregate government size as 9.52, -9.66, 20.59, 6.90 and -7.38 for 1981, 1991,

2001, 2010 and 2012 respectively with inflation rates responding as follows: 7.7 for 1981, 5.72

for 1991, 18.87 for 2001, 13.72 and 12.22 for 2012. Like many countries, industrialized and

developing, one of the most fundamental objectives of macroeconomic policies in Nigeria is to

sustain high economic growth together with low inflation. There is the need to highlight here that

Price stability does not portend static general price level of goods and services, but rather

simply suggests that the rate of such changes is such that it does not attract attention of

economic and policy agents. Steady increase in the general price level of goods and services

over a long time frame provides evidence of inflation spiral. It is of essence to appreciate that

volatility in the general price level erodes the power of money to function as a store of value. To

this extent, this will stunt savings, discourages investment, growth, and creates uncertainty and

distortions in the economy, to beget unreliable economic planning.

In order to remedy the undesirable economic syndrome, government has introduced a

lot of policy measures intended at controlling inflation which has plagued Nigeria since the

inception of the present guided deregulation. Of essence among the policy options is the fiscal

policy which involves the use of government expenditure and taxation for the control of inflation.

Meanwhile, government expenditure is the most frequently used instrument to pursue the

stabilization goal of fiscal policy. This may be attributed to the would-be adverse effect (which

may be counterproductive) of increase in tax for an economy where over 83% of its citizens are

living below the poverty line of $2.00 a day (WDI, 2012). Notwithstanding the intensity and

frequency of the use of this choice policy option, the rate of inflation still remains relatively very

high in Nigeria, meaning that inflation rate appears not to be substantially responsive to

adjustments in the levels of public expenditure. It is on the strength of this suspicion that we

consider it plausible to investigate the extent to which causal relationship exists between

innovations in government size and developments in inflation rate in Nigeria.

The main objective of this study is to investigate the causal relationship between

government size and inflation rate for the case of Nigeria. Nigeria has been battling with the two

digit inflation rates for a long period of time now. Specifically, we implement co-integration and

vector autoregressive analyses to test for the extent of existence of long-run relationship and

© BigBen


gauge the causal direction between government size and inflation rate respectively, for the

period of 31 years (1982-2013).

The scope of the study in terms time frame is constrained by our desire to decompose

public spending in Nigeria into four board sectors. This has limited the source of data to Central

Bank of Nigeria Statistical Bulletin and the time frame for the study due to the non availability of

such sectoral data before 1982.

The remaining part of this paper is structured as follows: Section 2 provides a brief

review of related literature, section 3 presents data and methodology, section 4 presents and

discuses the empirical results and section 5 the concluding remarks.

REVIEW OF RELATED LITERATURE

In this section, we review some the empirical works investigating inflation – government size

relationship. This is intended to provide guide for this study in terms of comparative analysis of

the results of studies of similar nature with that of this study and evaluation of the earlier studies

in this direction to afford the author the opportunity to identify the existing gap which provides

justification for the study.

Ezirim et al (2008), investigates the relationship between public expenditure growth and

inflation in the United States of America using the co integration analysis and Granger Causality

Model applied to Time Series Annual Data from 1970 – 2002. The results indicate that public

expenditure and inflation are co integrated and thus there exist a long-run equilibrium relation

between the two variables. Furthermore, the study identified a bi-causational relationship

between public expenditure growth and inflation in the United States of America. This result

suggests that while for the United States economy, public expenditure growth may be seen to

exacerbate inflationary pressures; such inflationary spiral also significantly influences public

expenditure decisions. This provides evidence that within the period under review in this study,

public expenditure growth was seen to have positive relationship existing between it and

inflationary pressures in the country. In effect, the efficacy of Keynesians proposition that sees

fiscal policy as a veritable tool to combating inflation in the developed countries is not violated

for United States. The study was carried out on a developed economy of the United States. In

the current study, we intend to replicate same in a developing economy like Nigeria with some

modifications for the purpose of comparison.

COSIMO (2011), Assesses the empirical evidence of the nexus between public

expenditure and inflation for the Mediterranean countries during the period 1970-2009, using a

time-series approach. A succinct survey of related econometric literature was undertaken by the

author before proceeding to the discussion of data and the econometric methodology.



Preliminary investigation of the suitability of the data employed for purposes intended, stationary

tests reveal, generally, that public expenditure/GDP ratio is stationary at first difference, i.e a I(1)

process, while prices index was found to be stationary only after two periods lag, i.e a I(2)

process. Results of the study identified a long-run relationship between the growth of public

expenditure and inflation for Portugal only. For the Granger causality tests, results revealed

evidence of uni-directional short-run causality flowing from expenditure to inflation for Cyprus,

Malta and Spain; and bidirectional causality, for Italy; and uni-directional causality flowing from

inflation to public expenditure for France. Certainly, this result is subject to the time period

examined, status of data employed and statistical methods used.

For Song & Casey (2008), it is commonly supposed in public and academic discourse

that inflation and big government are related. The authors explain that economic theory conveys

such a prediction only in special cases. At the instance of their results, they are of the view that

inflation is significantly positively related to the size of government mainly when periods of war

and peace are compared. Evidence delivered from their results indicated a weak positive

peacetime time series correlation between inflation and the size of government and further slips

into negative, the correlation between inflation and non-defense spending, putting cross-country

analysis into perspective.

Ozurumba (2012) examines the causal relationship between inflation and fiscal deficits

in Nigeria, covering the period 1970-2009. This was carried out by way of developing an

estimation model of inflation and fiscal deficit, with a view to testing causes and effects as well

as the relationship between them. The estimation technique used is the autoregressive

distributed lag (ARDL) model and the Granger-causality tests. Result of the Granger-causality

test revealed that the conjuncture that fiscal deficit does not cause inflation be rejected judging

from the fact that the result indicates a significant causal link flowing from fiscal deficits to

inflation spirals at less than 5 percent probability value. This suggests that fiscal deficits cause

inflation in Nigeria. From his results of the ARDL test, it was observed that there exists a

significant negative correlation between growth in fiscal deficit and innovations in the rate of

inflation which is in conformity with expectation. Abstracting from the results, the study

recommended that policies targeted at inflationary control in Nigeria may be most effective if

they are targeted at reduction in fiscal deficits and by extension, government should support

growth in the real sectors of the economy.

A study by Ezirim and Muoghalu (2006), suggests that the magnitude of government

size as a proportion of gross domestic product (GDP) reflects the level of taxation in the

economy. They were of the view that when the size of the public sector (measured by the share

of expenditure on GDP) exceeds a certain threshold, incentives to produce are discouraged

© BigBen


(because of high tax burden). According to them, this will lead reduction in aggregate supply,

scarcity of goods and services making for excess of demand over supply. The net effect of such

a bad adjustment between demand and supply is an inflationary spiral.

Muhammad & Attiya (2013) explores the relationship among the rate of inflation,

economic growth and government expenditure in case of Pakistan. They decomposed the

government expenditure into government current expenditure and the government development

expenditure and employed time series data for the period of 1980-2010 in the analysis.

Econometrics tools such as Augmented Dickey Fuller (ADF) unit root test, Autoregressive

Distributed Lag (ARDL) model, Johansen cointegration and Granger-causality tests were used

to gauge such relationships. The outcome of the estimations identified a long term relationship

amongst rate of inflation, economic growth and government expenditure; it means that

government expenditures yield positive externalities and linkages. The results further revealed

that in the short run time frame, inflation rate is found not to affect economic growth but rather

government expenditures is found to have link with economic growth. The causality test results

suggest that inflation rate cause economic growth with government expenditure also causing

economic growth in Pakistan.

Everton, Vincent & Wilson (2012) employed a modeling approach that incorporates the

theory of cointegration and its implied vector error correction model, to investigate the long term

relationship between fiscal deficits and inflation for Nigeria, a country which has experienced

very large fluctuations in the government fiscal deficits. The empirical results show that there is

a positive but insignificant relationship between fiscal deficits and inflation. This inconsequential

nature of the positive relationship between budget deficits and the inflation rate may result from

the fact that most a time fiscal deficits represent insignificant proportion public expenditure

which in several studies have been found to granger cause inflation rate. The analysis of the

Nigerian data also indicate a tenuous link to previous levels of fiscal deficits with inflation and

provide, moreover, evidence of a positive long-run relationship between money supply growth

and inflation, suggesting therefore that money supply growth is pro-cyclical and tends to grow at

a faster rate than the rate of inflation. Finally, from the impulse response and variance

decomposition analysis, the study finds that the length of inflation is an important determinant of

the ability of the system to return to its long-run equilibrium following a shock.

In the same, Medee, & Nenbee (2012) examined fiscal deficits and inflation in Nigeria for

the period of 30 years running from 1980 to 2010 tended at ascertaining the nature of the

relationships among inflation rate, interest rate and fiscal deficits. They employed the Ordinary

Least Square (OLS) estimation technique of multiple regressions in presenting the econometric

analysis of the study. The results showed that both inflation rates and interest rates were rightly



signed with fiscal deficits. Despite this theoretical congruence, inflation rates impacted on fiscal

deficits while interest rate does not. The authors were of the opinion that the inability of interest

rates to impact on fiscal deficits perhaps could be blamed on unstable macroeconomic policy

environment, corruption, and more. To this extent, they then, suggested that there is need to

reorder Nigeria’s fiscal policy priorities based on sincerity so as to rebuild confidence in the

economy. On the basis of the results the authors concluded that the current inflation targeting

policy regime, if any, should be implemented based on fiscal discipline, financial sector stability

as well as a reliable model for data computation of inflation. However the modeling approach of

the study where fiscal deficit is specified as a function of inflation rate and interest rate is viewed

with reservation. This stems from the fact that, the existence of a significant positive correlation

between interest rates and prices has been confirmed by erudite economic scholars (see,

Tooke, 1844, Gibson, 1923, Keynes, 1930, Kitchin 1923, Peake, 1928). In effect, the

independence of the explanatory variables cannot be vouched and to this extent the estimation

of the model may be frosted with or may not be absorbed of the problems of multi-colinearity,

positive autocorrelation and misspecification. This must have accounted for the low value R2 of

0.28 and meager DW static of 1.27.

Amir et al (2010) examines the causal relationship among government size, inflation and

economic growth for the period (1959-2007) in Iran. To test for the suitability of the employed

variable for the purposes intended, phillips-perron unit root test procedure was adopted for this

study. The results of the phillips-perron unit root test indicate that the three variables of interest

become stationary after differencing for one period which in effect suggests that the variables

are integrated of order one 1(1). The benchmark results indicate: (a) Existence of long-run

relationship among the variables as affirmed by cointegration test. (b) There is no causality

relationship between government size and GDP growth and negative unidirectional causality

running from economic growth to inflation were indicated by VEC model estimation. Another

result of the study shows that a decline in the government size may lead to low inflation without

any pressure on economic growth. The goal of most empirical studies in econometrics and other

social sciences is to determine whether a change in one variable causes a change in or helps to

predict another variable (Awe, 2008). To this extent, I am of the view that using variations or

developments in the employed variable may provide more precise prediction of the dependent

variables by the explanatory variables. In effect, the use of the absolute values of these

variables in the estimations by the authors of this study must have left the results of the

estimations or analysis tinted especially as no evidence of post estimation tests for stability of

the model, positive autocorrelation and misspecification as CUSUM and LM tests was present.

© BigBen


Most of the empirical studies reviewed in the course of this study, investigating the existence of

causal relationship between rate of inflation and government size were tested on developed

economies. To this extent, the author of this current study intends to replicate same in a

developing economy like Nigeria at least for comparative consideration. In the same vein, most

of the empirical reviews with respect to Nigeria economy were centered on the relationship

between fiscal deficits and the rate of inflation. This to the author would only amount to partial

estimation of public expenditure-inflation rate relationship thus painting partial picture of such an

all important correlation. My fear is a function of the fact that most a times, budget deficits may

constitute an insignificant proportion of gross public expenditure and therefore will not present a

through and fair view of the extent to which government size can fuel inflation rate in Nigeria.

Generally, all the empirical studies reviewed and documented here used the absolute values of

the variables within the period under review in investigating the causality. The goal of most

empirical studies in econometrics and other social sciences is to determine whether a change in

one variable causes a change in or helps to predict another variable (Awe, 2008). To this extent,

this study makes use of variations or developments in the employed variable for the

econometric analysis to provide more precise prediction of the dependent variables by the

explanatory variables. Finally, as never experienced in any of the studies reviewed above, this

study decomposes public expenditure in Nigeria into four major sectors in search of more robust

and informed fiscal policy decisions. All the above observations may have provided enough and

substantial gap to serve as motivation this study.

METHODOLOGY

This study is founded on Causal Comparative or Ex Post Facto Research Design bearing in

mind that the study attempts to explore cause and affect relationships where causes already

exist and cannot be manipulated. The study used what already exist and look backwards to

explain why. We seek to establish the causal relationship between inflation rate and government

size putting into perspective Nigeria economy. To achieve these fits, we opted to deploy the

relevant variables as follows: inflation rate (INFRATE) as the explained variable, and

government size (GOVTSIZE) decomposed into four subsectors of administration (ADMIN),

social and community services (SOCOS) economic services (ECONS) and transfers (TRFS) as

explanatory variables. GOVTSIZE means government expenditure as a percentage of GDP.

Annual data for the periods of 1981 to 2013 are sourced from the Central Bank of Nigeria (CBN)

statistical bulletin for 2013 published in 2014. The paper employs vector error correction

modeling, cointegration procedure, and causality tests to investigate the short run as well as

long run causal relationships between inflation and public expenditure growth in Nigeria.



Developments or variations in the data series employed expressed in percentage form are

deployed in the estimation. The latest analytical econometric application package software such

as E-View 7.0 is used frequently during the study.

Model Specification

Plethora of studies has established the fact that government size growth significantly fuels the

rate of inflation for both developed and developing economies (see Cosimo, 2011, Ezirim et al,

2008, Song & Casey, 2008, Ezirim & Muoghalu, 2006, Muhammad & Attiya, 2013, and Olaiya et

al amongst others). Here, the annual data on inflation spiral and government size for Nigeria for

the period of 1981 – 2013 are employed. The annual data on government size is decomposed

into the four major sectors or channels of government expenditures with the time series value

for each sector expressed as a percentage/proportion of GDP. To this extent we employ a

modeling approach that expresses inflation rate as a function of the decomposed government

size of, administration, social and community services, economic services and transfers as

follows:

INFRATE = (ADMIN, SCSERV, ECOSER, TRFS) (1)

For the purpose of estimation, the above functional notation is expressed in multivariate linear

model with intercept as follows:

INFRATEt = β0 + β1ADMINt + β2SCSERVt + β3ECOSERt + β4TRFSt + µt (2)

Where: INFRATE = inflation rate, ADMIN = administration, SCSERV = social and community

services, ECOSER = economic services and TRFS = transfers. β0 is the constant term, β1… β4

are the explanatory powers of the explanatory variables, t, is the time trend and µ is the

stochastic error term. In order to analyze the extent of the causal link between government size

as decomposed and inflation, we adopt the VAR modeling approach of (Amir et al., 2010). They

employed vector error correction (VEC 3, 2) model to test for the presence and the direction of

causal relationship among the three macroeconomic variables of inflation, GDP growth and

government size (in their aggregate values) for Iran. For this study we effect some modifications

such as omitting the GDP growth variable, decomposing government expenditure as proportion

of GDP into four major channels of public spending as identified above and taking the

percentage variations in them. Optimal lag length selection criteria suggest 2 (two) lags for both

Akaike Information Criterion (AIC) and Schwarz Bayesian Criterion (SBC) being guided by the

lag length which yields the smallest value for our information criterion, which brings our modif ied

model to VEC (5, 2). Equations (1-2) above were intended just to predict the linear function of

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the employed variables, but for the purpose of investigating the short and long run causal links

between consumer price index and government size as decomposed by sectors, system

equation in VEC environment was specified as below:

D(LCPI)=C(1)*(LCPI(-1)+3905.67289391*LADMIN_GDP(-1)-11524.236708*LSCSERV_GDP(-

1)+1443.19726024*LECOSERV_GDP(-1) + 1526.9975733*LTRANS_GDP(-1) -108.380704173

) + C(2)*D(LCPI(-1)) + C(3)*D(LCPI(-2))+C(4)*D(LADMIN_GDP(-1))+C(5)*D(LADMIN_GDP(-

2))+C(6)*D(LSCSERV_GDP(-1)) + C(7)*D(LSCSERV_GDP(-2))+C(8)*D(LECOSERV_GDP(-

1))+C(9)*D(LECOSERV_GDP(-2)) + C(10)*D(LTRANS_GDP(-1)) + C(11)*D(LTRANS_GDP(-2))

+ C(12) (3)

Where, C(1) is the coefficient of error correction term and speed of adjustment, C(2) …C(11)

are short run coefficients and C(12) the constant. LCPI is the log of consumer price index, while

LADMIN_GDP, LSCSERV_GDP, LECOSERV_GDP and LTRANS_GDP are the logs of the

ratios of public expenditure on administration, social and community service, economic services

and transfers respectively to GDP, while L indicates Logarithm.

Decision Rules

This is evaluated to determine the extent to which government size, as decomposed, jointly and

significantly cause consumer price index in the long run. The system equation is estimated

using Least Square method and result interpretation to be guided as follows:

(1) The C (1) is the long run coefficient of EC (-1). Then for long run causality to be established,

the value of C(1) must be negative and statistically significant at 5 percent margin of error,

(2) Then C(2),…, C(10) are the short run coefficients of the independent variables.

We evaluate these short run coefficients for short run causality running from the decomposed

government size by sectors to consumer price index using Wald Test through coefficient

diagnostic and restriction approach. If:

C(4)=C(5)=0, suggests that increase in government expenditure on administration does not

cause increase in consumer price index in the short run.

C(6)=C(7)=0, suggests that increase in government expenditure on social and community

service does not cause increase in consumer price index.

C(8)=C(9)=0, means that increase in government expenditure on economic services does not

cause increase in consumer price index in the short run.

C(10)=C(11)=0 indicates that there is no short run causality between government expenditure

on transfers and consumer price index.



Here, we describe the variables employed in the study. Consumer price index (CPI) is used to

proxy inflation spiral. Government expenditure on administration (ADMIN) represents public

expenditure on general Administration, Defense, Internal security and National Assembly. Public

expenditure on Social and Community Services (SCSERV) constitute government expenditures

on Education, Health and other social and community services. Expenses on Economic

Services (ECOSERV) means public expenditures on Agriculture, Construction, Transport &

Communication and other economic services, with public expenditure on Transfers (TRANS)

meaning government spending on Public debt servicing, Pensions and gratuity,

Contigencies/subventions and Other/Other CFR charges.

Estimation Procedure

For the purpose of diagnosing the employed variables for fitness and suitability for purposes

intended, E-view 7.0 econometric application package (software) was used to gauge the data

for stationarility or otherwise, employing the Augmented Dickey-Fuller and Phillip Peron (PP)

tests procedures. Whether long run relationship exists or otherwise, among the choice variables

is checked using co-integration analysis. Finally we ran granger non- causality test to establish

the direction of flow of influence between the explained and explanatory variables. Cosimo

(2011), the non-stationary series with the same order of integration may be cointegrated if there

exist some linear combination of the series that can be tested for stationarity. The Johansen and

Juselius procedure (Johansen, 1988; Johansen and Juselius, 1990) is preferable to test for

cointegration for more than two series. Moreover, Johansen and Juselius procedure is

considered better than Engle-Granger even in two time series case and has better small sample

properties since it allows feedback effects among the variables under investigation, where it is

assumed in the Engle and Granger procedure that there are no feedback effects between the

variables. The procedure is based on likelihood ratio (LR) test to determine the number of co-

integration vectors in the regression. Johansen technique enables us to test for the existence of

non-unique Co-integration relationships.

EMPIRICAL RESULTS

Data analysis and interpretation is intended to transform the data collected into credible

evidence about the development of the intervention. Data analysis involves working to uncover

patterns and trends in data sets while interpretation involves explaining those patterns and

trends. Data analysis is considered an important step and heart of the research in any research

work. When data has been collected with the assistance of relevant tools and methods, the next

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logical step, is to analyze and interpret the data with a view to arriving at empirical solution to

the problem.

Correlogram

We used this environment to verify the characteristics of the variables employed for the study by

gauging the levels of integration. Correlogram test was implemented for each of the variables of

LCP1, Ladmin_GDP, LSCServ_GDP, Lecoserv_GDP and Ltrans_GDP, for logs of consumer

price index, the ratios of government expenditure on administration to GDP, Social and

Community services to GDP, Economic services to GDP and transfers to GDP respectively. For

each of the correlogram test to determine the status of the variable in terms of stationarity, lag

length of 16 was implemented and the value of Q-statistic and their corresponding P-value at

lag 16 were read. At level, the P-values for all the variable were less than the 5 percent critical

level. This means that we accept the null hypothesis, which posits that the variable of interest is

not stationary at level. When the same process was followed to gauge the stationary level for

each of variables of interest at first difference, the P-values of the Q-statistic at lag 16 show that

in all the instances, the P-value was higher than 5 percent significant level excepting for log of

consumer price index which was stationary at second difference. Therefore, results of

correlogram used to test the series statistics, not presented here, affirm to the fact that in all

cases, the variables at least unit root, meaning that the variables are suitable for the purpose

intended.

Testing for Cointegration

It is frequently of interest to test whether a set of variables are co-integrated. This may be

desired because economic implications such as whether some systems are in equilibrium in the

long run or rather, it may appear sensible to test such hypothesis before estimating a

multivariate dynamic model (Engle & Granger, 1987). With stationarity confirmed for the entire

employed variable at first difference 1(1), excepting for the consumer price index (CPI) that is

stationary at 2nd difference. We are motivated to test for cointegration among the variables to

determine the number of Cointegrating equation, and hence gauge if there exist any long-run

equilibrium relationship between the explained and explanatory variables. There are several

methods (ordinary least squares, nonlinear least squares, maximum likelihood in an error

correction model, principal components, and canonical correlations) of estimating cointegrating

vectors, but examining the asymptotic distribution of the estimators resulting from these

methods shows that maximum likelihood in a fully specified error correction model (Johansen's

approach) has clearly better properties than the other estimators (Gonzalo, 1994). To this effect,



Trace and maximum eigenevalue approach by Johansen (1991, 1995) were preferred and

implemented. In the both instances the results indicate one Cointegrating equation, meaning

that all the variable share single error term, or that all the variables of LCPI, LADMIN_GDP,

LSCSERV_GDP, LECOSERV_GDP and LTRANS_GDP share long run associationship. This

by implication suggests that there is a long-run steady state equilibrium relationship existing

between the dependent and the independent variables. The results are presented in tables 2 &

3 below.

Table 1: Trace Test for Cointegration

Hypothesized No.

of CE(s)

Eigenvalue Trace Statistic 0.05

Critical value

Prob**

None* 0.7494 82.297 69.818 0.0036

At most 1 0.4555 40.777 47.856 0.1959

At most 2 0.4121 22.535 29.797 0.2696

At most 3 0.1730 6.596 15.494 0.6250

At most 4 0.0294 0.897 3.841 0.3434

Table 2: Maximum EigenvalueTest for Cointegration

Hypothesized

No. of CE(s)

Eigenvalue Max-Eigen

Statistic

0.05

Critical value

Prob**

None* 0.7494 41.519 33.876 0.0051

At most 1 0.4555 18.242 27.584 0.4751

At most 2 0.4121 15.939 21.131 0.2284

At most 3 0.1730 5.698 14.264 0.6522

At most 4 0.0294 0.897 3.841 0.3434

Notes: (i) Cointegration tests performed using Eview 7.0

(ii) both Trace and Max-Eigen tests indicate 1 cointegrating equations at the 0.05 level

(iii) * denotes rejection of the null hypothesis at the 0.05 level

Table 3: Estimates of Long-Run Co-integrating Vectors (Linearised)

LCPI LADMIN_GDP LSCSERV_GDP LECOSERV_GDP LTRANS_GDP

1.000000 3905.673 -15524.24 1443.197 1526.998

(1051.15) (2153.17) (364.827) (316.854)

Notes: 1. Figures in parentheses indicate standard errors.

2. The long run equilibrium relation is:

LCPI = 3905.673LADMIN_GDP – 11524.24LSCSERV_GDP + 1443.197LECOSERV_GDP +

1526.998LTRANS_GDP

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All the long run coefficients of the estimated model as are statistically significant as exhibited by

the long-run cointegrating vectors as expressed above.

Furthermore, evidence from the long run equilibrium relation suggests that excepting for

the ratio of public expenditures on social and community services to GDP, all the other

components of public expenditure GDP ratios are positively related with consumer price index

(CPI) in the long run time horizon. This by implication signifies that consumer price index and

government expenditures on economic services (ECOSERV), administration (ADMIN) and

transfers trend together on a positive notes in the long run, while public expenditures on social

and community services (SCSERV) share negative association with consumer price index in the

same time horizon. This is neither abnormal nor leaves cause for concern for a developing

economy like Nigeria with very high level of unemployment and substantial low level of average

installed manufacturing capacity utilization (AIMCU).

Testing for Long-run and Short run Causality in the VECM Environment

Testing for Long-run Causality

Table 4: Least Square Estimation of System Equation

Dependent Variable: D(LCPI)

Method of Least Square

Included observations: 30 after adjustments

Coefficient Std. Error t-Statistic Prob.

C(1) 0.014617 0.016669 0.876879 0.3921

C(2) 0.770504 0.251389 3.064988 0.0067

C(3) 0.095243 0.259889 0.366476 0.7183

C(4) 0.355437 87.31400 0.004071 0.9968

C(5) -0.049603 93.80084 -0.000529 0.9996

C(6) 109.2831 150.7290 0.725031 0.4778

C(7) 119.9015 131.0891 0.914657 0.3725

C(8) -67.96378 52.63503 -1.291227 0.2130

C(9) -26.34242 42.27395 -0.623136 0.5410

C(10) -12.83653 33.38631 -0.384485 0.7051

C(11) 14.40685 28.37673 0.507700 0.6178

C(12) 0.924354 0.834264 1.107987 0.2825

R-squared 0.809812 Mean dependent var 4.475646

Adjusted R-squared 0.693586 S.D. dependent var 4.055926

S.E. of regression 2.245143 Akaike info criterion 4.744590

Sum squared resid 90.73205 Schwarz criterion 5.305069

Log likelihood -59.16885 Hannan-Quinn criter. 4.923892

F-statistic 6.967570 Durbin-Watson stat 2.009618

Prob(F-statistic) 0.000171



The identification of a co-integrating vector among the variables, advised us to develop and

implement vector error correction model (VECM) to investigate if there exist any significant long-

run and/or short-run causal relationship between the dependent and independent variables. The

guiding objective of this study is the evaluation of the direction of the causal relationship

between consumer price index and sectorally decomposed government size. To achieve this fit,

we develop system equation from the restricted VAR estimate of the target equation and

estimate same in the least square environment to obtain the values of both long-run and short-

run coefficients with their respective P-values. To establish the existence or otherwise of long-

run and/or short run causalities and observe the long run and short run coefficient values from

the least square estimations. The coefficient value of the error term lagged one period EC(-1) is

used to gauge if government size as decomposed by sector jointly and significantly cause

consumer price index in the long run. For this to be affirmed, the coefficient of EC (-1) must be

negative and at the same time statistically significant. The results of the least square estimation

of the VEC model as presented in table 5 above, show that the coefficient and (probability

value) of the error correction term, C (1) are 0.014617 (0.3921) respectively. These suggest that

the condition precedent for confirmation of causality in the long run is violated as the coefficient

of error correction term is positive and the p-value of 39.21 percent is higher than the 5 percent

significant level, meaning that we cannot reject the null hypothesis, which states that there is no

long run causality running from government size as decomposed by sector to consumer price

index in Nigeria. On the above note, we declare that for Nigeria, public spending on

administration, social and community services, economic services and transfers as ratios of

GDP jointly do not influence consumer price index on the long run.

Testing for Short run Causality

To gauge for the extent to which short-run causal relationship exists between consumer price

index (CPI) and government size as decomposed by sectors, we implement the Wald test

through Coefficient diagnostic and restriction to test the null hypotheses which state that the

value of the coefficient of each variable and its lags, jointly are not significantly different from

zero, meaning that there is no short-run causality between that variable and the dependent

variable within the period under review. This test is performed on each of the independent

variables and our decision guided by the Chi-square values and the corresponding p-values.

High p-value above the 5 percent significant level advises us not to reject the null hypothesis

and low p-value below the 5 percent significant level advises us to reject the null hypothesis. At

this point, we use WALD test developed by Toda and Yamamoto (1995) and Dolado &

Lütkepohl (1996) to implement linear coefficient restriction to establish whether or not causality

© BigBen


runs from any of the independent variables to the dependent variable. The results of the WALD

tests for causality as presented in tables 6 to 9 below indicate as follows: (i) LADMIN_GDP(-1)

and LADMIN_GDP(-2) jointly do not influence the consumer price index. (ii) The Chi-Square

value of 0.923948(0.6300) with the figure in bracket indicating the P-value, means that we

cannot reject the null hypothesis that LSCSERV_GDP (-1) and LSCSERV_GDP (-2) jointly

cannot cause consumer price index in Nigeria. (iii) With the Chi-Square (P-value) of

1.684034(0.4308) respectively, we cannot reject the null hypothesis that LECOSERV_GDP(-1)

and LECOSERV_GDP(-2) jointly do not cause consumer price index within the period under

review. (iv) Finally, the Chi-Square (P-value) of 0.629969(0.7298) respectively suggests that we

cannot reject the null hypothesis, meaning that LTRANS-GDP(-1) and LTRANS_GDP(-2) jointly

cannot influence consumer price index in Nigeria. The above results, suggest that there is no

short run causality running from government size as decomposed to consumer price index.

Table 5: Wald Test

For Equation: C(4)D(LADMIN-GDP(-1))=C(5)D(LADMIN-GDP(-2))=0

Test Statistic Value df Probability

F-statistic

Chi-square

1.11E-05

2.22E-05

(2, 18)

2

1.0000

1.0000

NULL Hypothesis: C(4)=C(5)=0

NULL Hypothesis Summary:

Normalized Restriction (0) Value Std. Err

C(4)

C(5)

.355437

-049603

87.31400

93.80084

Table 6: Wald Test

For Equation: C(6)D(LSCSERV-GDP(-1))=C(7)D(SCSERV-GDP(-2))=0


F-statistic

Chi-square

0.461974

0.923948

(2, 18)

2

0.6373

0.6300




C(6)

C(7)

109.2831

119.9015

150.7290

131.0891



Table 7: Wald Test

For Equation: C(8)D(LECOSERV-GDP(-1))=C(9)D(ECOSERV-GDP(-2))=0


F-statistic

Chi-square

0.842017

1.684034

(2, 18)

2

0.4471

0.4308




C(8)

C(9)

-67.96378

-26.34242

87.31400

93.80084

Table 8: Wald Test

For Equation: C(10)D(LTRANS-GDP(-1))=C(11)D(LTRANS-GDP(-2))=0


F-statistic

Chi-square

0.314984

0.629969

(2, 18)

2

0.7337

0.7298




C(10)

C(11)

-12.83653

14.40685

33.86631

28.37673

Discussion of Results

This section is dedicated to evaluation of the results of the data analysis in confirming or failing

to reject the null hypothesis as reported. This is done in terms of the dispositions of the theories

guiding the study and relevant documented extant empirical literature. Summary of this model

estimation indicate that: (1) Evidence from the cointegration test shows that LCPI,

LADMIN_GDP, LSCSERV_GDP, LECOSERV_GDP and LTRANS_GDP share long run

associationship on the positive note, excepting for expenditure on the social and community

services (LSCSERV_GDP) which is negatively signed. This means that, in the long run, when

government expenditure on administration, economic services and transfers, severally goes up,

consumer price index goes up and when government expenditure on social and community

service sector goes up, in the long run, consumer price index goes down. (2) The independent

variables of LADMIN_GDP, LSCSERV_GDP, LECOSERV_GDP and LTRANS_GDP jointly do

not cause consumer price index (LCPI) in the long run, meaning that, in the long run,

developments in the independent variables cannot explain the variations in the dependent

variable in this model. (3) Finally, no evidence of short run causality running from each of the

© BigBen


independent variables to the dependent variable was identified in this model, meaning that even

in the short run, public expenditures on administration, social and community service, economic

services and transfers, severally cannot influence consumer price index.

The results of the estimations appear to be mixed and contradicting and leave us with no

other option than to reflect in the concept of exegeneity in statistical or econometric modeling. In

any modeling approach, there are two sides to the issue of exegeneity: (1) Variable or factor

exogenous in the model which refers to the independent variable identified within the structure

of the model. (2) Variables or factors exogenous to the model which refers to variables relevant

to the model but is out of the model (omitted in the specification), may be because of their

nature (qualitative etc). The fact that ceteris is never paribus in practice; the two categories of

exogenous variables may jointly or severally explain developments in dependent variable of a

model. Reviewing the overall results of the study in terms of the identified cointegrating equation

and the granger non causality tests, suggest that developments in the exogenous factors or

variables outside the model rather those in the model, have dominated in explaining or causing

developments in the consumer price index within the period under investigation.

Furthermore, for economics, all different variables affect the same variable

simultaneously as repeated experiments under control are infeasible. To this extent the two

most difficult challenges are that: (1) Correlation does not imply causality and distinguishing

between these two is by no means an easy task. (2) There always exists the possibility of

ignored common factors and the causal relationship among variables might disappear when the

previously ignored common causes are considered (Jin-Lung, 2008).Granger representation

theorem by Engle & Granger (1987) and Johansen (1991) postulates that “existence of co-

integration implies that granger causality must exist in at least one direction between the

variables of the system”. These results contradict this theorem because despite the fact that 1

co-integrating vector was identified with all the long run coefficients statistically significant,

neither evidence of short run or long run granger non causality between the dependent and

independent variables is identified, meaning the developments in the consumer price index is a

function exogenous variables or factor outside the estimation model. This may include the

exchange rate of the domestic currency, the Naira, to the United States Dollars (Ogbonna,

2009, 2010). In the both instances, evidence from the studies, identified exchange rate as a

singular most promising macroeconomic fundamental for both internal and external balance

adjustments. Other studies such as Dakurah et al., 2001, Abizadeh & Yousefi, 1998 also failed

to identify any significant association between public expenditure growth and consumer price

index.



Furthermore, the P-value of LCPI(-1) coefficient of 0.0067 which is far below the significant

value of 5 percent, suggests that developments in consumer price index in Nigeria is a function

of its previous period values and exchange rate of the domestic currency to the United States

dollar. The efficacy of broad money supply may have been neutralizes by the ever high lending

rate which always leaves the deposit money banks with excess liquidity. In effect, the much

touted assumption by policy makers that government size, particularly the cost of governance

cause inflation as proxied by consumer price index is not supported by the enquiry, but rather

the value of inflation in the previous period (inflationary expectations), exchange rate of the

domestic currency to the US dollar and other relevant exogenous factors outside the estimated

model significantly influence developments in consumer price index in Nigeria.

To vouch for the reliability and avoid dwelling on dubious results for decision or opinion,

relevant diagnostic tests were implemented and the results indicate as following: The result of

normalcy test of Jarque-Bera coefficient of 0.651808(0.721875) with the figure in bracket

indicating the P-value, suggests that the null hypothesis which states residuals are normally

distributed cannot be rejected, meaning that the residuals of the estimated equations are

normally distributed. The result of the Breusch-Godfrey (LM) test for serial correlation, show

Chi-Square probability value of 0.3562, suggesting non rejection of the null hypothesis of no

serial correction, meaning that our model is not characterized by serial correlation. This

assertion is further supported by the value of the Durbin-Watson statistic of 2.009618. Equally,

we implemented ARCH model estimation to test for heteroscedasticity effect on our system

equation. The result of Obs*R-square value of 4.273296 and Prob. Chi-Square(1) value 0.0387

suggests the rejection of the null hypothesis of heteroscedasticity effect on the model, meaning

that there is no heteroskedasticity effect on the estimated regression equation. Finally, the

stability of the model is verified with the recursive residual wandering within the 5 percent critical

lines in the CUSUM test for equation stability. With all these confirmatory tests, the suitability

and validity of the estimation regression model is established, meaning that the results of the

estimation model can be relied upon for relevant policy decisions.

CONCLUDING REMARKS

This paper employs autoregressive modeling, cointegration procedure, and causality tests to

investigate the relationships between public expenditure as decomposed by sector and inflation

in Nigeria. The unit roots test indicates that the variables were relatively stationary when

transformed into rates of change. Results of correlogram used to test for stationary level, affirm

to the fact that in all cases, the variables become stationary at least in their first difference,

meaning that the variables are suitable for the purpose intended. The results further indicate

© BigBen


that: (i) Long run equilibrium relationship exist between consumer price index and the

decomposed government size in Nigeria, with all the long run coefficients statistically significant.

(ii) No long run causal relationship was identified between consumer price index and the

decomposed government expenditure within the period under investigation, meaning that for

Nigeria, public spending on administration, social and community services, economic services

and transfers as ratios of GDP jointly do not influence consumer price index on the long run. (iii)

There is no short run causality running from LADMIN_GDP, LSCSERV_GDP,

LECOSERV_GDP or LTRANS_GDP to the dependent variable (LCPI), meaning that

government sectoral expenditures on administration, social and community services, economic

services and transfers, severally do not influence consumer price index in the short-run in

Nigeria. The above results present some policy implications that government of Nigeria cannot

comfortably regulate the levels of inflation in the economy with controlling the levels of its

expenditures. This suggests that fiscal policy in the form of government expenditure should not

be intended to moderate developments in consumer price index, rather, Policy measures

designed to ensure effective and appropriate pricing of the domestic currency should be put in

place for effective moderation of inflation in Nigeria.

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